Data Science
Skill Tests Library

Tests to Measure and Assess All Data Science Skills

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Data Storytelling Skills Test

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Increasing data visualization represented by a line graph

Data Governance Skills Test

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A pair of dice sitting on top of each other

Probability Skills Test

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A pie chart showing the relationship between data, statistics, and insights

Inferential Statistics Online Test

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A visual representation of data using a segmented pie chart

Data Visualization Skills Test

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Pencil poised to mark checked boxes on a checklist

Data Science Aptitude Test

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The Python logo, a stylized snake-shaped

Python Coding Test (High)

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Laptop with a graph on the screen showcasing data analysis and insights

SAP BI Test (Business Intelligence)

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A visual representation of data insights using a gold bar graph

Microsoft BI Test

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A circle with a cloud in the middle and the words big data written in the middle

Big Data Assessment Test

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Black and orange Apache Spark logo

Spark Test

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Computer monitor displaying a graph, representing data analysis and analytics

Data Science & Analytics Test

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Laptop with data model diagram on screen, representing data modeling

Data Modeling Test

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A pickaxe and a graph on a clipboard symbolize the process of extracting valuable insights from data.

Data Mining Test

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Blue eye reflecting a DNA strand, symbolizing data insights and connections

Apache Cassandra Test

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Want to build a high-performing team of data science experts?

Start testing candidates now

Use our data science skill assessment tests to screen and hire candidates for positions such as:

Data science engineer Data architect Associate data analyst
Deep learning engineer Python analyst Data analyst
Data science developer Python developer Data analyst (specialist)
Deep learning research engineer Research analyst Machine learning developer
Data science associate Business analyst Machine learning expert
Deep learning developer Machine learning engineer Machine learning specialist

For recruiting data scientists, our data science live coding interview and coding assessment help to measure the following skills:

  • Data Science with R - Machine learning techniques, analytics, and data manipulation
  • Data Science with Python - Packages, scripts, modules, nested loops, and strings
  • Introduction to Data Science
  • Introduction to Statistics
  • Data Visualization
  • Exploratory Data Analysis
  • Regression Analysis
  • Subprocess Module
  • Random Module
  • Regular Expressions
  • Built-in Functions
  • Command-Line Arguments
  • Extended Iterable Unpacking
  • Python Implementations
  • Neural Networks
  • Regression Analysis - Linear regression and non-linear regression
  • Pattern Recognition - Clustering
  • Data Exploration

Two important use cases for Data Science skill assessment test:

#1 Identifying job-fit candidates based on job roles

You can build customized data science skill assessments for any given job role. Using this capability, you can choose questions from different skill types, including functional, technical, and soft skills. For example, with our customized data scientist coding assessment, you can assess candidates' understanding of Data Extraction and Mining, Numerical Ability, Interactive Reporting, Python Coding, and Machine Learning and hire the best individuals for the job.

#2 Skill-gap analysis of your employees

iMocha allows you to trace employees' skill competency through data science training assessments. It determines the current skill level and identifies the areas for growth. Using this feature, you can measure employees' progress from their existing knowledge base to gained knowledge. For example, you can use our data science training assessments to identify an engineer's knowledge about Sampling Distribution, SQLite Coding, Quantitative Aptitude, and other skills and perform a skill gap analysis.

Test Creation Process

We provide various types of data scientist hiring tests to help you evaluate candidates' specific skills. These questions are created by Subject Matter Experts (SMEs) based on their knowledge and expertise. For example, only Data Science specialists will develop questions about Data Manipulation using R or Machine Learning based on easy, medium, and hard difficulty levels.

You can - choose which questions to include in the Data Scientist coding test or ask us to create personalized assessments according to your requirements.

Loved by our

Identifying the right candidate remotely took a lot of our time, considering how each seemed to have different levels of skills and expertise.

iMocha helped us to transform our remote hiring strategy and cut down on our candidate filtration time by 40% making it our preferred assessment software.

Pedro Furtado

Capacity Manager,

Hiring Data Scientists was a challenge as the interview process took time. With iMocha's data science assessments, the process was simplified.

The tool helped us shortlist top candidates and extend offer letter in just 4 days.

Lynn Hodak

Talent Acquisition Manager, Capgemini

We have always believed in hiring talent on merit rather than resumes. When we started our global recruitment, we were clear on including assessments to evaluate skills and shortlist candidates.

iMocha has helped us immensely over the past 3 years to not only assess candidates but also optimize our recruitment process.

Senthil Nayagam K

Sr. VP, Hexaware

How is Data science skill assessment customized?
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Our SMEs can create individualized assessments depending on your job role requirements. These assessments are divided into primary and secondary skills, such as Data Extraction, Data Visualization, Regression Analysis, Quantitative Aptitude, Optimizing Functions, Reporting, and more. Additionally, SMEs can craft customized questions according to applicants' experience and difficulty level.

Ready to Hire a Data Scientist? Check out our pro tips!

What are the certifications required for this role?
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Some popular Certifications for Data science related job roles are as follows:

• Microsoft Certified: Azure Data Scientist Associate

• IBM Data Science Professional Certificate

• Google Professional Data Engineer Certification

• Cloudera Certified Professional (CCP) Data Engineer

• SAS Certified AI & Machine Learning Professional

• TensorFlow Developer Certificate

• Open Certified Data Scientist (Open CDS)

• Principal Data Scientist (PDS)

• Certified Analytics Professional (CAP)

• HarvardX Data Science Professional Certificate

What are the most common interview questions for this role?
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Some of the common data science interview questions asked for this role are:

• Why is normal distribution important?

• Can you use machine learning for time series analysis?

• What is a lambda function in Python?

• What is a hyperplane in SVM?

• How is memory managed in Python?

Want more data science interview questions? Here is a list of 100+ data science interview questions you can ask data science professionals.

What are the roles and responsibilities of a Data science engineer?
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Data science engineers are required to perform the following tasks and responsibilities:

• Should be able to collect data and identify its data source

• Analyze both structured and unstructured data

• Create workflows to solve the business problems

• Collaborate with the team to develop data strategies

• Know how to combine various algorithms

• Should have the ability to utilize data visualization techniques and tools

• Present AI/ML solutions for business processes and outcomes

• Monitor data pipelines and conduct knowledge-sharing sessions for effective data use

• Conduct data mining and extraction for valuable data sources

• Analyze enterprise databases to simplify and improve product development

• Develop the organization’s test model quality and A/B testing framework

Elevate your hiring game with our winning data scientist job description template!

What are the required skill sets of Data science engineers?
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You can consider these technical as well as non-technical skills while hiring Data science engineers:

Technical Skills:

  • Data Visualization
  • Statistical Analysis
  • Machine Learning and AI
  • Deep Learning
  • Data Wrangling
  • Programming
  • Big Data
  • Processing Large Data
  • Web Scraping
  • Database Management
  • Data Mining

Non-Technical Skills:

  • Data Intuition
  • Problem-solving skills
  • Interpersonal skills
  • Communication skills
  • Mathematics
  • Probability
  • Excel
  • Collaboration
  • Decision-making
  • Detail Oriented
  • Logical Reasoning

Explore both primary and secondary Data Scientist skills to enhance your talent identification process.

What is the package of Data science engineer?
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In the United States, the average Data science engineer salary is $124,244 per year. Entry-level Data science engineers' salaries start at $97,462 per year.

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